Abstract: Provided is an authentication device comprising: a data acquisition unit that acquires spherical data including a video of a person taken by a fisheye camera; and an authentication performing unit that performs facial recognition performed by a spherical convolutional neural network on the spherical data. Provided is an authentication device comprising: a data acquisition unit that acquires spherical data including a video of a person taken by a fisheye camera; and an authentication performing unit that performs facial recognition performed by a convolutional neural network on a sub-image after extracting, from the spherical data, the sub-image of a portion of a face of the person, adjusting an orientation of the face of the person in the sub-image, and applying, on the sub-image, a distortion correction process that corrects distortion generated by the fisheye camera.

Abstract: A method for detecting forgery in facial recognition is disclosed that comprises selecting (110) an illumination pattern including at least three illumination intensities; controlling (120) a light-emitting device (220) to emit light pulses, according to the illumination pattern; capturing (130) with a camera (210) a respective image of an eye region (15) of a face (10) during each emitted light pulse; determining (140) whether a glint (20) is present in the eye region (15) of each captured image; measuring (150) a glint intensity of each determined glint (20); extracting (160) a respective numerical feature for each captured image, the numerical feature representing a curve of all measured glint intensities at the glint intensity of the respective image; and outputting (180) a signal that the face (10) is forged, if one or more of the extracted numerical features does not correspond to a reference numerical feature.

Abstract: An accessibility determination device may include an imaging device that captures images of a surrounding environment of a user at time intervals to acquire a plurality of captured images; a facial organ detector that analyzes the captured images to detect a facial organ of a person that makes a notification to the user when the accessibility determined by processor satisfies a predetermined criterion and the target detector detects that the person is the predetermined target person. The processor may change the accessibility or the predetermined criterion depending on a distance between the imaging device and the person.

Abstract: New software systems and capabilities that facilitate the rapid development, evaluation, and deployment of advanced inspection and detection systems using high-fidelity synthetic imagery. The present invention generates high-fidelity synthetic imagery for detection systems that analyze data across the electromagnetic spectrum in an automated, random, directed, or semi-directed manner.

Abstract: A system for sorting seeds based on their resistance to a stress is disclosed. Batches of purified seeds sorted using the system are also disclosed.

Abstract: A text processing method and apparatus, an electronic device, and a storage medium. The method includes: according to a coordinate value of each pixel in a text image, determining a plurality of center pixels of the text image and an adjacent pixel of each center pixel (S1); acquiring a coordinate value of each center pixel, a spatial offset of the adjacent pixel of each center pixel, and the width of a pixel processing area (S2); acquiring position information of each adjacent pixel according to the coordinate value of each center pixel, the spatial offset of the adjacent pixel of each center pixel, the width of the pixel processing area, and a preset vector calculation formula (S3); and acquiring a text of the text image according to the position information and a preset mask mapping relationship (S4).

Abstract: An agricultural implement includes a ground-engaging tool and a computing system. In this respect, the computing system is configured to determine a surface profile of a portion of a field positioned aft of the ground-engaging tool based on the image data generated by a first imaging device. Moreover, the computing system is configured to determine a surface profile of a portion of the field positioned forward of the ground-engaging tool based on the image data generated by a second imaging device. In addition, the computing system is configured to determine when the ground-engaging tool is plugged based on the surface profile of the portion of the field positioned aft of the ground-engaging tool and the surface profile of the portion of the field positioned forward of the ground-engaging tool.

Abstract: A video content providing method and a video content providing device are provided. The method includes the following. A wide viewing angle image stream and a corresponding first audio content are obtained. A plurality of regions of interest in the wide viewing angle image stream are determined, and candidate regions in the regions of interest are integrated into a first frame. A designated region is selected from the candidate regions, and a corresponding first audio component are found from the first audio content. Each first audio component is suppressed to adjust the first audio content into a second audio content. The first frame and the second audio content are integrated into a specific video content, and the specific video content is provided.

Abstract: Disclosed are a display device system and a method for adaptively enhancing an image quality. The method includes: acquiring an original image, performing iterative detail enhancement processing on the original image by utilizing at least one filter function containing iteratively-updated filter parameters, in a case that a difference between a quality evaluation score of the input image and a quality evaluation score of the detail-enhanced image of the ith iteration satisfies an iteration condition, obtaining filter parameters of an (i+1)th iteration by updating the filter parameters of the ith iteration, and continuing to perform detail enhancement processing on the input image by utilizing at least one filter function containing the filter parameters of the (i+1)th iteration, until a difference between the quality evaluation score of the input image and a quality evaluation score of a detail-enhanced image of the (i+1)th iteration satisfies the iteration condition.

Abstract: Methods and system for guiding user data capture during a scan of a vehicle using a mobile device are disclosed. A user may scan a vehicle using a camera or other sensors of the mobile device to capture data from which a three-dimensional virtual model may be generated. During the scanning process, models may be generated and evaluated according to quality metrics. Visual cues may be determined and presented to the user during scanning to indicate areas sufficiently scanned or areas requiring additional scanning to meet data quality requirements for model generation. Damage to vehicle components may be identified by analysis of the generated model, and addition data capture or user annotation entry may be directed based upon the identified damage.

Abstract: Systems and methods may include tracking one or a plurality features across a decreasing scale of tiled sets of one or more images. Aspects may include generating point data for each of the tracked features based on a coordinate system relative to the first camera or the second camera, and transforming the point data to a Global Positioning System/Inertial Navigation System (GPS/INS) coordinate system based on (1) an origin of a first GPS device coupled to the first camera and (2) a rotation of the first camera relative to an INS device coupled to the first camera. Aspects may include generating, based on the transformed point data, a geodetic mapping function, determining, based on the geodetic mapping function, georegistered coordinates of the tracked features, using the georegistered coordinates of the tracked features to characterize the water flow.

Abstract: A collation system of the present invention includes imaging means for acquiring a captured image of a pre-passage side area with respect to each of gates arranged in parallel with each other, and collation means for performing a collation process on the captured image of the pre-passage side area for each of the gates, between a previously registered target and a target included in the captured image. The collation means performs the collation process on the basis of a target in the captured image corresponding to one of the gates and a target in the captured image corresponding to another one of the gates.

Abstract: Disclosed herein are systems, methods, devices, and media for carrying out detection of ophthalmic and systemic diseases and disorders. Deep learning algorithms enable the automated analysis of ophthalmic images such as retinal scans to generate accurate detection of various diseases and disorders. Point-of-care implementations allow for rapid and efficient detection outside of the clinical setting.

Abstract: A collation system of the present invention includes imaging means for acquiring a captured image of a pre-passage side area with respect to each of gates arranged in parallel with each other, and collation means for performing a collation process on the captured image of the pre-passage side area for each of the gates, between a previously registered target and a target included in the captured image. The collation means performs the collation process on the basis of a target in the captured image corresponding to one of the gates and a target in the captured image corresponding to another one of the gates.

Abstract: A system for enabling spot cleaning includes a mobile computing device and a mobile cleaning robot. The mobile computing device includes at least one camera configured to capture images of an environment, and at least one data processor configured to (a) establish a coordinate system in the environment, (b) determine a first set of coordinates of a region at a first location, (c) determine a second set of coordinates of a mobile cleaning robot at a second location, (d) send the first set of coordinates and second set of coordinates, or coordinates of the first location relative to the second location, to the mobile cleaning robot, and (e) send an instruction to the mobile cleaning robot to request the mobile cleaning robot to travel to the first location.

Abstract: The disclosure relates to a wind turbine blade inspection system and method based on an unmanned aerial vehicle. The system includes: a collection module, used for collecting blade data and surrounding environment data of blades to be inspected, determining feature inspection points of the unmanned aerial vehicle according to the blade data and the surrounding environment data, and generating inspection paths; an inspection module, used for shooting corresponding blade at the feature inspection points according to the inspection paths to obtain a first inspection image and a second inspection image; an analysis module, used for receiving the first inspection image and the second inspection image, analyzing the first inspection image and the second inspection image to obtain a health state of the corresponding blade, and making a maintenance plan according to the health state of each of the blades.

Abstract: A method, apparatus and system for generating sensor data comprising a subset of tagged sensor data. The method includes: sensing, using a sensing element, ambient data, wherein the ambient data characterises a condition of an environment proximate to the sensing element; identifying, using a data identification engine, at least a first subset of the ambient data comprising a representation of, or identifying information related to, personally relevant information obtained by the sensing element; tagging, using a data tagging engine, the first subset of the ambient data with at least one data tag; and outputting, via the communication interface, at least a second subset of the ambient data comprising ambient data that has not been tagged by the data tagging engine.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for production line conformance monitoring. For example, certain embodiments of the present invention utilize systems, methods, and computer program products that perform production line conformance monitoring by utilizing categorical validation machine learning models that are generated using a plurality of training production line images associated with a related category subset of a plurality of validation categories for a target validation category.

Abstract: A system for the detection and classification of live microorganisms in a sample includes a light source and an incubator holding one or more sample-containing growth plates. A translation stage moves the image sensor and/or the growth plate(s) along one or more dimensions to capture time-lapse holographic images of microorganisms. Image processing software executed by a computing device captures time-lapse holographic images of the microorganisms or clusters of microorganisms on the one or more growth plates. The image processing software is configured to detect candidate microorganism colonies in reconstructed, time-lapse holographic images based on differential image analysis. The image processing software includes one or more trained deep neural networks that process the time-lapsed image(s) of candidate microorganism colonies to detect true microorganism colonies and/or output a species associated with each true microorganism colony.

Abstract: In particular embodiments, a computing system may access a plurality of images for pre-training a first machine-learning model that includes an encoder and a decoder. Using each image, the system may pre-train the model by dividing the image into a set a patches, selecting a first subset of the patches to be visible and a second subset of the patches to be masked during the pre-training, processing, using the encoder, the first subset of patches to generate corresponding first latent representations, processing, using the decoder, the first latent representations corresponding to the first subset of patches and mask tokens corresponding to the second subset of patches to generate reconstructed patches corresponding to the second subset of patches, the reconstructed patches and the first subset of patches being used to generate a reconstructed image, and updating the model based on comparisons between the image and the reconstructed image.